71 research outputs found
Communication-constrained feedback stability and Multi-agent System consensusability in Networked Control Systems
With the advances in wireless communication, the topic of Networked Control Systems (NCSs) has become an interesting research subject. Moreover, the advantages they offer convinced companies to implement and use data networks for remote industrial control and process automation. Data networks prove to be very efficient for controlling distributed systems, which would otherwise require complex wiring connections on large or inaccessible areas. In addition, they are easier to maintain and more cost efficient. Unfortunately, stability and performance control is always going to be affected by network and communication issues, such as band-limited channels, quantization errors, sampling, delays, packet dropouts or system architecture. The first part of this research aims to study the effects of both input and output quantization on an NCS. Both input and output quantization errors are going to be modeled as sector bounded multiplicative uncertainties, the main goal being the minimization of the quantization density, while maintaining feedback stability. Modeling quantization errors as uncertainties allows for robust optimal control strategies to be applied in order to study the accepted uncertainty levels, which are directly related to the quantization levels. A new feedback law is proposed that will improve closed-loop system stability by increasing the upper bound of allowed uncertainty, and thus allowing the use of a coarser quantizer. Another aspect of NCS deals with coordination of the independent agents within a Multi-agent System (MAS). This research addresses the consensus problem for a set of discrete-time agents communicating through a network with directed information flow. It examines the combined effect of agent dynamics and network topology on agents\u27 consensusability. Given a particular consensus protocol, a sufficient condition is given for agents to be consensusable. This condition requires the eigenvalues of the digraph modeling the network topology to be outer bounded by a fan-shaped area determined by the Mahler measure of the agents\u27 dynamics matrix
Distributed Optimal Control and Application to Consensus of Multi-Agent Systems
This paper develops a novel approach to the consensus problem of multi-agent
systems by minimizing a weighted state error with neighbor agents via linear
quadratic (LQ) optimal control theory. Existing consensus control algorithms
only utilize the current state of each agent, and the design of distributed
controller depends on nonzero eigenvalues of the communication topology. The
presented optimal consensus controller is obtained by solving Riccati equations
and designing appropriate observers to account for agents' historical state
information. It is shown that the corresponding cost function under the
proposed controllers is asymptotically optimal. Simulation examples demonstrate
the effectiveness of the proposed scheme, and a much faster convergence speed
than the conventional consensus methods. Moreover, the new method avoids
computing nonzero eigenvalues of the communication topology as in the
traditional consensus methods
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